一、获取代码方式
获取代码方式1：
完整代码已上传我的资源：【数据融合】基于matlab拓展卡尔曼滤波IMU和GPS数据融合【含Matlab源码 1600期】
获取代码方式2：
通过订阅紫极神光博客付费专栏，凭支付凭证，私信博主，可获得此代码。
备注：订阅紫极神光博客付费专栏，可免费获得1份代码（有效期为订阅日起，三天内有效）；
二、部分源代码
%for testingclcclearclose allpauseLen = 0;%%Initializations%TODO: load data heredata = load('lib/IMU_GPS_GT_data.mat');IMUData = data.imu;GPSData = data.gpsAGL;gt = data.gt;addpath([cd, filesep, 'lib'])initialStateMean = eye(5);initialStateCov = eye(9);deltaT = 1 / 30; %hope this doesn't cause floating point problemsnumSteps = 500000;%TODO largest timestamp in GPS file, divided by deltaT, cast to intresults = zeros(7, numSteps);% time x y z Rx Ry Rz% sys = system_initialization(deltaT);Q = blkdiag(eye(3)*(0.35)^2, eye(3)*(0.015)^2, zeros(3));%IMU noise characteristics%Using default values from pixhawk px4 controller%https://dev.px4.io/v1.9.0/en/advanced/parameter_reference.html%accel: first three values, (m/s^2)^2%gyro: next three values, (rad/s)^2 filter = filter_initialization(initialStateMean, initialStateCov, Q);%IMU noise? do in filter initializationIMUIdx = 1;GPSIdx = 1;nextIMU = IMUData(IMUIdx, :); %first IMU measurementnextGPS = GPSData(GPSIdx, :); %first GPS measurement%plot ground truth, raw GPS data% plot ground truth positionsplot3(gt(:,2), gt(:,3), gt(:,4), '.g')grid onhold on% plot gps positions% plot3(GPSData(:,2), GPSData(:,3), GPSData(:,4), '.b')axis equalaxis vis3dcounter = 0;MAXIGPS = 2708;MAXIIMU = 27050;isStart = false;for t = 1:numStepscurrT = t * deltaT;if(currT >= nextIMU(1)) %if the next IMU measurement has happened% disp('prediction')filter.prediction(nextIMU(2:7));isStart = true;IMUIdx = IMUIdx + 1;nextIMU = IMUData(IMUIdx, :);% plot3(filter.mu(1, 5), filter.mu(2, 5), filter.mu(3, 5), 'or');endif(currT >= nextGPS(1) & isStart) %if the next GPS measurement has happened% disp('correction')counter = counter + 1;filter.correction(nextGPS(2:4));GPSIdx = GPSIdx + 1;nextGPS = GPSData(GPSIdx, :);plot3(nextGPS(2), nextGPS(3), nextGPS(4), '.r');% plot3(filter.mu(1, 5), filter.mu(2, 5), filter.mu(3, 5), 'ok');% plotPose(filter.mu(1:3, 1:3), filter.mu(1:3, 5), filter.mu(1:3,4));endresults(1, t) = currT;results(2:4, t) = filter.mu(1:3, 5); %just position so far%plot3(results(2, t), results(3, t), results(4, t), 'or');%disp(filter.mu(1:3, 1:3));if pauseLen == infpause;elseif pauseLen > 0pause(pauseLen);endif IMUIdx >= MAXIIMU || GPSIdx >= MAXIGPSbreakendendplot3(results(2,:), results(3,:), results(4,:), '.b');% xlim([-10 10]);% ylim([-10 10]);xlabel('x, m');ylabel('y, m');zlabel('z, m');%% Evaluationgps_score = evaluation(gt, GPSData)results_eval = results.';score = 0;estimation_idx = 1;count = 0; for i = 2:length(gt)score = score + norm(gt(i, 2:4) - results_eval(30 * (i-1), 2:4)) ^ 2;count = count + 1;endcountscore = sqrt(score / count)%% Function
三、运行结果
四、matlab版本及参考文献
1 matlab版本
a
2 参考文献
[1] 沈再阳.精通MATLAB信号处理[M].清华大学出版社，.
[2]高宝建,彭进业,王琳,潘建寿.信号与系统——使用MATLAB分析与实现[M].清华大学出版社，.
[3]王文光,魏少明,任欣.信号处理与系统分析的MATLAB实现[M].电子工业出版社，.
如果觉得《【数据融合】基于matlab拓展卡尔曼滤波IMU和GPS数据融合【含Matlab源码 1600期】》对你有帮助，请点赞、收藏，并留下你的观点哦！
